mlsanityData to 7 Oct 2026

EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification

arXiv 2310.09754 ↗First posted 15 Oct 2023cs.AIcited by 36

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Abstract (arXiv)

Fact verification aims to automatically probe the veracity of a claim based on several pieces of evidence. Existing works are always engaging in accuracy improvement, let alone explainability, a critical capability of fact verification systems. Constructing an explainable fact verification system in a complex multi-hop scenario is consistently impeded by the absence of a relevant, high-quality dataset. Previous datasets either suffer from excessive simplification or fail to incorporate essential considerations for explainability. To address this, we present EXFEVER, a pioneering dataset for multi-hop explainable fact verification. With over 60,000 claims involving 2-hop and 3-hop reasoning, each is created by summarizing and modifying information from hyperlinked Wikipedia documents. Each instance is accompanied by a veracity label and an explanation that outlines the reasoning path supporting the veracity classification. Additionally, we demonstrate a novel baseline system on our EX-FEVER dataset, showcasing document retrieval, explanation generation, and claim verification, and validate the significance of our dataset. Furthermore, we highlight the potential of utilizing Large Language Models in the fact verification task. We hope our dataset could make a significant contribution by providing ample opportunities to explore the integration of natural language explanations in the domain of fact verification.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). Builds on 33 of its 50 references that are in the map. First posted on arXiv 15 Oct 2023.

Builds on

33 of 50 references.

References · 33

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2022Training language models to follow instructions with human feedbackcited by 15,712
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  5. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  6. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  7. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,040
  8. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
  9. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  10. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
  11. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  12. 2020Fact or Fiction: Verifying Scientific Claimscited by 546
21 more
  1. 2018e-SNLI: Natural Language Inference with Natural Language Explanationscited by 468
  2. 2017"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detectioncited by 361
  3. 2020Explainable Automated Fact-Checking for Public Health Claimscited by 209
  4. 2020HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verificationcited by 199
  5. 2020Answering Complex Open-Domain Questions with Multi-Hop Dense Retrievalcited by 160
  6. 2023Fact-Checking Complex Claims with Program-Guided Reasoningcited by 146
  7. 2019Towards Debiasing Fact Verification Modelscited by 143
  8. 2020Generating Fact Checking Explanationscited by 132
  9. 2019Fine-grained Fact Verification with Kernel Graph Attention Networkcited by 105
  10. 2019GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verificationcited by 100
  11. 2023The science of fake newscited by 94
  12. 2019Reasoning Over Semantic-Level Graph for Fact Checkingcited by 69
  13. 2019Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QAcited by 63
  14. 2020FakeCovid -- A Multilingual Cross-domain Fact Check News Dataset for COVID-19cited by 60
  15. 2021Fool Me Twice: Entailment from Wikipedia Gamificationcited by 50
  16. 2020Multi-Hop Fact Checking of Political Claimscited by 37
  17. 2021Generating Fluent Fact Checking Explanations with Unsupervised Post-Editingcited by 15
  18. 2023MenatQA: A New Dataset for Testing the Temporal Comprehension and Reasoning Abilities of Large Language Modelscited by 15
  19. 2021A Multi-Level Attention Model for Evidence-Based Fact Checkingcited by 13
  20. 2021Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehensioncited by 10
  21. 2022QCRI's COVID-19 Disinformation Detector: A System to Fight the COVID-19 Infodemic in Social Mediacited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 7; 2025: 13; 2026: 15.

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  1. 2025A Survey of LLM-based Deep Search Agents: Paradigm, Optimization, Evaluation, and Challengescited by 58
  2. 2025ReportBench: Evaluating Deep Research Agents via Academic Survey Taskscited by 34
  3. 2024Claim Verification in the Age of Large Language Models: A Surveycited by 23
  4. 2025A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applicationscited by 21
  5. 2024Generative Large Language Models in Automated Fact-Checking: A Surveycited by 19
  6. 2024FinDVer: Explainable Claim Verification over Long and Hybrid-Content Financial Documentscited by 19
  7. 2023Assessing Knowledge Editing in Language Models via Relation Perspectivecited by 15
  8. 2024Beyond Relevance: Evaluate and Improve Retrievers on Perspective Awarenesscited by 12
  9. 2025CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?cited by 11
  10. 2024Does Knowledge Localization Hold True? Surprising Differences Between Entity and Relation Perspectives in Language Modelscited by 8
  11. 2026DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agentcited by 8
  12. 2025Veri-R1: Toward Precise and Faithful Claim Verification via Online Reinforcement Learningcited by 5
24 more
  1. 2025Long-Form Information Alignment Evaluation Beyond Atomic Factscited by 4
  2. 2025Coordinating Search-Informed Reasoning and Reasoning-Guided Search in Claim Verificationcited by 4
  3. 2025Detecting Corpus-Level Knowledge Inconsistencies in Wikipedia with Large Language Modelscited by 4
  4. 2024Navigating the Noisy Crowd: Finding Key Information for Claim Verificationcited by 3
  5. 2025STRIVE: Structured Reasoning for Self-Improvement in Claim Verificationcited by 3
  6. 2025GraphCheck: Multipath Fact-Checking with Entity-Relationship Graphscited by 2
  7. 2025GRITHopper: Decomposition-Free Multi-Hop Dense Retrievalcited by 2
  8. 2025Misinformation Detection using Large Language Models with Explainabilitycited by 2
  9. 2026LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detectioncited by 2
  10. 2026DecomposeRL: Learning to Ask Useful, Informative, and Diverse Questions for Semi-Supervised, Traceable Claim Verificationcited by 2
  11. 2024FarExStance: Explainable Stance Detection for Farsicited by 1
  12. 2026Toward Reliable, Safe, and Secure LLMs for Scientific Applicationscited by 1
  13. 2026When Misinformation Speaks and Converses: Rethinking Fact-Checking in Audio Platformscited by 1
  14. 2026From Articles to Premises: Building PrimeFacts, an Extraction Methodology and Resource for Fact-Checking Evidencecited by 1
  15. 2026Diagnosing LLM Arbitration Behavior over Pre-evidence Epistemic States in RAG-based Fact-Checkingcited by 1
  16. 2026AgentGrad: Intervention-guided Prompt Optimization for Multi Agent Systemscited by 1
  17. 2025Graph-of-Causal Evolution: Challenging Chain-of-Model for Reasoningcited by 0
  18. 2026MisSpans: Fine-Grained False Span Identification in Cross-Domain Fake Newscited by 0
  19. 2026FactNet: A Billion-Scale Knowledge Graph for Multilingual Factual Groundingcited by 0
  20. 2026Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimizationcited by 0
  21. 2026An Empirical Analysis of Factual Errors in Human-Written Text and Its Application to Factual Error Detectioncited by 0
  22. 2026ReflectFact: Self-Reflective Agents for Improving Comprehension and Reasoning in Multi-Hop Fact Verificationcited by 0
  23. 2026Sycophancy Suppression Can Impair Rational Updating: Anti-Sycophancy Should Preserve the Ability to Updatecited by 0
  24. 2026ARAFA: An LLM-Generated Arabic Fact-Checking Datasetcited by 0

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  1. 2025Fact in Fragments: Deconstructing Complex Claims via LLM-based Atomic Fact Extraction and Verification
  2. 2025Reasoning Paths as Signals: Augmenting Multi-hop Fact Verification through Structural Reasoning Progression
  3. 2025Hybrid Fact-Checking that Integrates Knowledge Graphs, Large Language Models, and Search-Based Retrieval Agents Improves Interpretable Claim Verification
  4. 2023Evidence-based Interpretable Open-domain Fact-checking with Large Language Models
  5. 2024Retrieval Augmented Fact Verification by Synthesizing Contrastive Arguments
  6. 2024CHECKWHY: Causal Fact Verification via Argument Structure
  7. 2024JustiLM: Few-shot Justification Generation for Explainable Fact-Checking of Real-world Claims
  8. 2026R2VC: Modular Fact-Checking with Retrieval, Verification, and Confidence Calibration